Some longitudinal PBMC timepoints were relabelled after this analysis was conducted. These are the corrected timepoints: P106: W48 -> W49 P109: W48 -> W49 P110: W38 -> W48 P111: W40 -> W41
These timepoints are synonyms: Pre-vaccine <-> Post-nivolumab
Set up workspace
# Libraries library (dplyr)
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ forcats 1.0.0 ✔ readr 2.1.5
✔ ggplot2 3.5.1 ✔ stringr 1.5.1
✔ lubridate 1.9.4 ✔ tibble 3.2.1
✔ purrr 1.0.4 ✔ tidyr 1.3.1
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
Set pseudo count for in vitro samples
Set a pseudo count to allow for in vitro fold change calculations of undetected clones The appropriate value was explored in file “Test_pseudocount_frequency.Rmd” and the slides titled “Testing pseudocounts in calculating fold change”
Open TCR reactivity data
<- read.csv ("/jsimonlab/users/chloetu/melanoma/Melanoma_Eryn/analysis_093024/Eryn_reactivity_results/reformatted_reconstructed_TCR_072324.csv" ) %>% mutate (Beta_clonotype = paste0 (TRBV_1, ";" , TRBJ_1, ";" , CDR3B_1)) %>% select (Beta_clonotype, Patient, Reactive) %>% filter (Reactive == "Yes" )%>% :: count (Patient)
Patient n
1 101 3
2 103 3
3 104 18
4 108 7
Compile P101’s data
Load longitudinal frequencies
# Control == pretreatment <- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/101pre-treament_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )# Post-Nivo == prevax <- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/101pre-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )# Post-vaccine <- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/101post-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )
Aggregate beta chains into one dataframe
<- p101_pretreatment_beta %>% full_join (p101_prevax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p101_pretreatment" = "Freq.x" ,"p101_prevax" = "Freq.y" ,"p101_pretreatment_umi" = "totalUMICount.x" ,"p101_prevax_umi" = "totalUMICount.y" ) %>% full_join (p101_postvax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p101_postvax" = "Freq" ,"p101_postvax_umi" = "totalUMICount" ) %>% select ("v_hit" , "j_hit" , "cdr3" , "p101_pretreatment" , "p101_pretreatment_umi" , "p101_prevax" , "p101_prevax_umi" , "p101_postvax" , "p101_postvax_umi" ) %>% mutate_at (c ("p101_pretreatment" , "p101_prevax" , "p101_postvax" ), as.numeric) %>% unite ("Beta_clonotype" , c (v_hit, j_hit, cdr3), sep = ";" )dim (p101_betas_pbmc)
Calculate fold changes across longitudinal timepoints
<- p101_betas_pbmc %>% mutate (postvax_vs_prevax_fc = p101_postvax/ p101_prevax,prevax_vs_pretreatment_fc = p101_prevax/ p101_pretreatment,log2fc_postvax_vs_prevax = log2 (postvax_vs_prevax_fc),log2fc_prevax_vs_pretreatment = log2 (prevax_vs_pretreatment_fc))
Load in vitro frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/101-DMSO_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/101-PoolA_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/101-PoolB_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )
Aggregate beta chains into one dataframe
<- full_join (p101DMSO_beta,p101poolA_beta,by= "Beta_clonotype" ) %>% :: rename ("p101_DMSO_beta" = Freq.x, "p101_DMSO_umi" = totalUMICount.x, "p101_poolA_beta" = Freq.y,"p101_poolA_umi" = totalUMICount.y) %>% full_join (p101poolB_beta,by= "Beta_clonotype" ) %>% :: rename ("p101_poolB_beta" = Freq,"p101_poolB_umi" = totalUMICount)%>% distinct (Beta_clonotype) %>% dplyr:: count ()
Convert to decimal frequency to %
<- p101_betas_pbmc %>% mutate (p101_pretreatment = p101_pretreatment * 100 ,p101_postvax = p101_postvax * 100 ,p101_prevax = p101_prevax * 100 )<- p101_betas_invitro %>% mutate (p101_DMSO_beta = p101_DMSO_beta * 100 ,p101_poolA_beta = p101_poolA_beta * 100 ,p101_poolB_beta = p101_poolB_beta * 100 )
Join longitudinal and in vitro frequencies by beta chain
<- full_join (p101_betas_pbmc, p101_betas_invitro)
Joining with `by = join_by(Beta_clonotype)`
Calculate fold changes across in vitro samples
<- p101_betas %>% rowwise () %>% mutate (poolA_vs_dmso_fc = sum (c (p101_poolA_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p101_DMSO_beta, pseudo_freq), na.rm = TRUE ),poolB_vs_dmso_fc = sum (c (p101_poolB_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p101_DMSO_beta, pseudo_freq), na.rm = TRUE )) %>% ungroup () %>% mutate (log2fc_poolA_vs_dmso = log2 (poolA_vs_dmso_fc),log2fc_poolB_vs_dmso = log2 (poolB_vs_dmso_fc),max_log2fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ log2fc_poolA_vs_dmso,>= log2fc_poolA_vs_dmso ~ log2fc_poolB_vs_dmso),max_fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ poolA_vs_dmso_fc,>= log2fc_poolA_vs_dmso ~ poolB_vs_dmso_fc))
Attach TCR reactivities to dataframe via the beta clonotype
<- reactivity %>% filter (Patient == "101" )<- p101_betas %>% mutate (Reactive = case_when (Beta_clonotype %in% p101_reactive$ Beta_clonotype ~ TRUE ,! (Beta_clonotype %in% p101_reactive$ Beta_clonotype) ~ FALSE ))
Save data
write.csv (p101_betas, "p101_betas_merged_Part1.csv" , row.names = FALSE )
Compile P103’s data
Load longitudinal frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/103pre-treatment_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/103pre-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/103post-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/103wk48_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) <- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/103wk72_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )
Aggregate beta chains into one dataframe
<- p103_pretreatment_beta %>% full_join (p103_prevax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p103_pretreatment" = "Freq.x" ,"p103_prevax" = "Freq.y" ,"p103_pretreatment_umi" = "totalUMICount.x" ,"p103_prevax_umi" = "totalUMICount.y" ) %>% full_join (p103_postvax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p103_postvax" = "Freq" ,"p103_postvax_umi" = "totalUMICount" ) %>% full_join (p103_w48_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p103_w48" = "Freq" ,"p103_w48_umi" = "totalUMICount" ) %>% full_join (p103_w72_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p103_w72" = "Freq" ,"p103_w72_umi" = "totalUMICount" ) %>% select ("v_hit" , "j_hit" , "cdr3" , "p103_pretreatment" , "p103_pretreatment_umi" , "p103_prevax" , "p103_prevax_umi" , "p103_postvax" , "p103_postvax_umi" , "p103_w48" , "p103_w48_umi" , "p103_w72" , "p103_w72_umi" ) %>% mutate_at (c ("p103_pretreatment" , "p103_pretreatment_umi" , "p103_prevax" , "p103_prevax_umi" , "p103_postvax" , "p103_postvax_umi" , "p103_w48" , "p103_w48_umi" , "p103_w72" , "p103_w72_umi" ), as.numeric) %>% unite ("Beta_clonotype" , c (v_hit, j_hit, cdr3), sep = ";" )dim (p103_betas_pbmc)
Calculate fold changes across longitudinal timepoints
<- p103_betas_pbmc %>% mutate (postvax_vs_prevax_fc = p103_postvax/ p103_prevax,prevax_vs_pretreatment_fc = p103_prevax/ p103_pretreatment,log2fc_postvax_vs_prevax = log2 (postvax_vs_prevax_fc),log2fc_prevax_vs_pretreatment = log2 (prevax_vs_pretreatment_fc))
Load in vitro frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/103-DMSO_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/103-PoolA_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/103-PoolB_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )
Aggregate beta chains into one dataframe
<- full_join (p103DMSO_beta,p103poolA_beta,by= "Beta_clonotype" ) %>% :: rename ("p103_DMSO_beta" = Freq.x, "p103_DMSO_umi" = totalUMICount.x, "p103_poolA_beta" = Freq.y,"p103_poolA_umi" = totalUMICount.y) %>% full_join (p103poolB_beta,by= "Beta_clonotype" ) %>% :: rename ("p103_poolB_beta" = Freq,"p103_poolB_umi" = totalUMICount)%>% distinct (Beta_clonotype) %>% dplyr:: count ()
Convert to decimal frequency to %
<- p103_betas_pbmc %>% mutate (p103_pretreatment = p103_pretreatment * 100 ,p103_postvax = p103_postvax * 100 ,p103_prevax = p103_prevax * 100 ,p103_w48 = p103_w48 * 100 ,p103_w72 = p103_w72 * 100 )<- p103_betas_invitro %>% mutate (p103_DMSO_beta = p103_DMSO_beta * 100 ,p103_poolA_beta = p103_poolA_beta * 100 ,p103_poolB_beta = p103_poolB_beta * 100 )
Join longitudinal and in vitro frequencies by beta chain
<- full_join (p103_betas_pbmc, p103_betas_invitro)
Joining with `by = join_by(Beta_clonotype)`
Calculate fold changes across in vitro samples
<- p103_betas %>% rowwise () %>% mutate (poolA_vs_dmso_fc = sum (c (p103_poolA_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p103_DMSO_beta, pseudo_freq), na.rm = TRUE ),poolB_vs_dmso_fc = sum (c (p103_poolB_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p103_DMSO_beta, pseudo_freq), na.rm = TRUE )) %>% ungroup () %>% mutate (log2fc_poolA_vs_dmso = log2 (poolA_vs_dmso_fc),log2fc_poolB_vs_dmso = log2 (poolB_vs_dmso_fc),max_log2fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ log2fc_poolA_vs_dmso,>= log2fc_poolA_vs_dmso ~ log2fc_poolB_vs_dmso),max_fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ poolA_vs_dmso_fc,>= log2fc_poolA_vs_dmso ~ poolB_vs_dmso_fc))
Attach TCR reactivities to dataframe via the beta clonotype
<- reactivity %>% filter (Patient == "103" )<- p103_betas %>% mutate (Reactive = case_when (Beta_clonotype %in% p103_reactive$ Beta_clonotype ~ TRUE ,! (Beta_clonotype %in% p103_reactive$ Beta_clonotype) ~ FALSE ))
Save data
write.csv (p103_betas, "p103_betas_merged_Part1.csv" , row.names = FALSE )
Compile P104’s data
Load longitudinal frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/104pre-treament_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/104pre-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/104post-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/104wk48_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )
Aggregate beta chains into one dataframe
<- p104_pretreatment_beta %>% full_join (p104_prevax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p104_pretreatment" = "Freq.x" ,"p104_prevax" = "Freq.y" ,"p104_pretreatment_umi" = "totalUMICount.x" ,"p104_prevax_umi" = "totalUMICount.y" ) %>% full_join (p104_postvax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p104_postvax" = "Freq" ,"p104_postvax_umi" = "totalUMICount" ) %>% full_join (p104_w48_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p104_w48" = "Freq" ,"p104_w48_umi" = "totalUMICount" ) %>% select ("v_hit" , "j_hit" , "cdr3" , "p104_pretreatment" , "p104_pretreatment_umi" , "p104_prevax" , "p104_prevax_umi" , "p104_postvax" , "p104_postvax_umi" , "p104_w48" , "p104_w48_umi" ) %>% mutate_at (c ("p104_pretreatment" , "p104_pretreatment_umi" , "p104_prevax" , "p104_prevax_umi" , "p104_postvax" , "p104_postvax_umi" , "p104_w48" , "p104_w48_umi" ), as.numeric) %>% unite ("Beta_clonotype" , c (v_hit, j_hit, cdr3), sep = ";" )dim (p104_betas_pbmc)
Calculate fold changes across longitudinal timepoints
<- p104_betas_pbmc %>% mutate (postvax_vs_prevax_fc = p104_postvax/ p104_prevax,prevax_vs_pretreatment_fc = p104_prevax/ p104_pretreatment,log2fc_postvax_vs_prevax = log2 (postvax_vs_prevax_fc),log2fc_prevax_vs_pretreatment = log2 (prevax_vs_pretreatment_fc))
Load in vitro frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/104-DMSO_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/104-PoolA_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/104-PoolB_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )
Aggregate beta chains into one dataframe
<- full_join (p104DMSO_beta,p104poolA_beta,by= "Beta_clonotype" ) %>% :: rename ("p104_DMSO_beta" = Freq.x, "p104_DMSO_umi" = totalUMICount.x, "p104_poolA_beta" = Freq.y,"p104_poolA_umi" = totalUMICount.y) %>% full_join (p104poolB_beta,by= "Beta_clonotype" ) %>% :: rename ("p104_poolB_beta" = Freq,"p104_poolB_umi" = totalUMICount)%>% distinct (Beta_clonotype) %>% dplyr:: count ()
Convert to decimal frequency to %
<- p104_betas_pbmc %>% mutate (p104_pretreatment = p104_pretreatment * 100 ,p104_postvax = p104_postvax * 100 ,p104_prevax = p104_prevax * 100 ,p104_w48 = p104_w48 * 100 )<- p104_betas_invitro %>% mutate (p104_DMSO_beta = p104_DMSO_beta * 100 ,p104_poolA_beta = p104_poolA_beta * 100 ,p104_poolB_beta = p104_poolB_beta * 100 )
Join longitudinal and in vitro frequencies by beta chain
<- full_join (p104_betas_pbmc, p104_betas_invitro)
Joining with `by = join_by(Beta_clonotype)`
Calculate fold changes across in vitro samples
<- p104_betas %>% rowwise () %>% mutate (poolA_vs_dmso_fc = sum (c (p104_poolA_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p104_DMSO_beta, pseudo_freq), na.rm = TRUE ),poolB_vs_dmso_fc = sum (c (p104_poolB_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p104_DMSO_beta, pseudo_freq), na.rm = TRUE )) %>% ungroup () %>% mutate (log2fc_poolA_vs_dmso = log2 (poolA_vs_dmso_fc),log2fc_poolB_vs_dmso = log2 (poolB_vs_dmso_fc),max_log2fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ log2fc_poolA_vs_dmso,>= log2fc_poolA_vs_dmso ~ log2fc_poolB_vs_dmso),max_fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ poolA_vs_dmso_fc,>= log2fc_poolA_vs_dmso ~ poolB_vs_dmso_fc))
Attach TCR reactivities to dataframe via the beta clonotype
<- reactivity %>% filter (Patient == "104" )<- p104_betas %>% mutate (Reactive = case_when (Beta_clonotype %in% p104_reactive$ Beta_clonotype ~ TRUE ,! (Beta_clonotype %in% p104_reactive$ Beta_clonotype) ~ FALSE ))
Save data
write.csv (p104_betas, "p104_betas_merged_Part1.csv" , row.names = FALSE )
Compile P105’s data
Load longitudinal frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/105pre-treament_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/105pre-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/105post-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/105wk48_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )
Aggregate beta chains into one dataframe
<- p105_pretreatment_beta %>% full_join (p105_prevax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p105_pretreatment" = "Freq.x" ,"p105_prevax" = "Freq.y" ,"p105_pretreatment_umi" = "totalUMICount.x" ,"p105_prevax_umi" = "totalUMICount.y" ) %>% full_join (p105_postvax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p105_postvax" = "Freq" ,"p105_postvax_umi" = "totalUMICount" ) %>% full_join (p105_W48_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p105_w48" = "Freq" ,"p105_w48_umi" = "totalUMICount" ) %>% select ("v_hit" , "j_hit" , "cdr3" , "p105_pretreatment" , "p105_pretreatment_umi" , "p105_prevax" , "p105_prevax_umi" , "p105_postvax" , "p105_postvax_umi" , "p105_w48" , "p105_w48_umi" ) %>% mutate_at (c ("p105_pretreatment" , "p105_pretreatment_umi" , "p105_prevax" , "p105_prevax_umi" , "p105_postvax" , "p105_postvax_umi" , "p105_w48" , "p105_w48_umi" ), as.numeric) %>% unite ("Beta_clonotype" , c (v_hit, j_hit, cdr3), sep = ";" )dim (p105_betas_pbmc)
Calculate fold changes across longitudinal timepoints
<- p105_betas_pbmc %>% mutate (postvax_vs_prevax_fc = p105_postvax/ p105_prevax,prevax_vs_pretreatment_fc = p105_prevax/ p105_pretreatment,log2fc_postvax_vs_prevax = log2 (postvax_vs_prevax_fc),log2fc_prevax_vs_pretreatment = log2 (prevax_vs_pretreatment_fc))
Load in vitro frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/105-DMSO_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/105-PoolA_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/105-PoolB_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )
Aggregate beta chains into one dataframe
<- full_join (p105DMSO_beta,p105poolA_beta,by= "Beta_clonotype" ) %>% :: rename ("p105_DMSO_beta" = Freq.x, "p105_DMSO_umi" = totalUMICount.x, "p105_poolA_beta" = Freq.y,"p105_poolA_umi" = totalUMICount.y) %>% full_join (p105poolB_beta,by= "Beta_clonotype" ) %>% :: rename ("p105_poolB_beta" = Freq,"p105_poolB_umi" = totalUMICount)%>% distinct (Beta_clonotype) %>% dplyr:: count ()
Convert to decimal frequency to %
<- p105_betas_pbmc %>% mutate (p105_pretreatment = p105_pretreatment * 100 ,p105_postvax = p105_postvax * 100 ,p105_prevax = p105_prevax * 100 ,p105_w48 = p105_w48 * 100 )<- p105_betas_invitro %>% mutate (p105_DMSO_beta = p105_DMSO_beta * 100 ,p105_poolA_beta = p105_poolA_beta * 100 ,p105_poolB_beta = p105_poolB_beta * 100 )
Join longitudinal and in vitro frequencies by beta chain
<- full_join (p105_betas_pbmc, p105_betas_invitro)
Joining with `by = join_by(Beta_clonotype)`
Calculate fold changes across in vitro samples
<- p105_betas %>% rowwise () %>% mutate (poolA_vs_dmso_fc = sum (c (p105_poolA_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p105_DMSO_beta, pseudo_freq), na.rm = TRUE ),poolB_vs_dmso_fc = sum (c (p105_poolB_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p105_DMSO_beta, pseudo_freq), na.rm = TRUE )) %>% ungroup () %>% mutate (log2fc_poolA_vs_dmso = log2 (poolA_vs_dmso_fc),log2fc_poolB_vs_dmso = log2 (poolB_vs_dmso_fc),max_log2fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ log2fc_poolA_vs_dmso,>= log2fc_poolA_vs_dmso ~ log2fc_poolB_vs_dmso),max_fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ poolA_vs_dmso_fc,>= log2fc_poolA_vs_dmso ~ poolB_vs_dmso_fc))
Save data
write.csv (p105_betas, "p105_betas_merged_Part1.csv" , row.names = FALSE )
Compile P106’s data
Load longitudinal frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/106pre-treament_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/106pre-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/106post-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/106wk48_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )
Aggregate beta chains into one dataframe
<- p106_pretreatment_beta %>% full_join (p106_prevax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p106_pretreatment" = "Freq.x" ,"p106_prevax" = "Freq.y" ,"p106_pretreatment_umi" = "totalUMICount.x" ,"p106_prevax_umi" = "totalUMICount.y" ) %>% full_join (p106_postvax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p106_postvax" = "Freq" ,"p106_postvax_umi" = "totalUMICount" ) %>% full_join (p106_w48_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p106_w48" = "Freq" ,"p106_w48_umi" = "totalUMICount" ) %>% select ("v_hit" , "j_hit" , "cdr3" , "p106_pretreatment" , "p106_pretreatment_umi" , "p106_prevax" , "p106_prevax_umi" , "p106_postvax" , "p106_postvax_umi" , "p106_w48" , "p106_w48_umi" ) %>% mutate_at (c ("p106_pretreatment" , "p106_pretreatment_umi" , "p106_prevax" , "p106_prevax_umi" , "p106_postvax" , "p106_postvax_umi" , "p106_w48" , "p106_w48_umi" ), as.numeric) %>% unite ("Beta_clonotype" , c (v_hit, j_hit, cdr3), sep = ";" )dim (p106_betas_pbmc)
Calculate fold changes across longitudinal timepoints
<- p106_betas_pbmc %>% mutate (postvax_vs_prevax_fc = p106_postvax/ p106_prevax,prevax_vs_pretreatment_fc = p106_prevax/ p106_pretreatment,log2fc_postvax_vs_prevax = log2 (postvax_vs_prevax_fc),log2fc_prevax_vs_pretreatment = log2 (prevax_vs_pretreatment_fc))
Load in vitro frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/106-DMSO_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/106-PoolA_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/106-PoolB_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )
Aggregate beta chains into one dataframe
<- full_join (p106DMSO_beta,p106poolA_beta,by= "Beta_clonotype" ) %>% :: rename ("p106_DMSO_beta" = Freq.x, "p106_DMSO_umi" = totalUMICount.x, "p106_poolA_beta" = Freq.y,"p106_poolA_umi" = totalUMICount.y) %>% full_join (p106poolB_beta,by= "Beta_clonotype" ) %>% :: rename ("p106_poolB_beta" = Freq,"p106_poolB_umi" = totalUMICount)%>% distinct (Beta_clonotype) %>% dplyr:: count ()
Convert to decimal frequency to %
<- p106_betas_pbmc %>% mutate (p106_pretreatment = p106_pretreatment * 100 ,p106_postvax = p106_postvax * 100 ,p106_prevax = p106_prevax * 100 ,p106_w48 = p106_w48 * 100 )<- p106_betas_invitro %>% mutate (p106_DMSO_beta = p106_DMSO_beta * 100 ,p106_poolA_beta = p106_poolA_beta * 100 ,p106_poolB_beta = p106_poolB_beta * 100 )
Join longitudinal and in vitro frequencies by beta chain
<- full_join (p106_betas_pbmc, p106_betas_invitro)
Joining with `by = join_by(Beta_clonotype)`
Calculate fold changes across in vitro samples
<- p106_betas %>% rowwise () %>% mutate (poolA_vs_dmso_fc = sum (c (p106_poolA_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p106_DMSO_beta, pseudo_freq), na.rm = TRUE ),poolB_vs_dmso_fc = sum (c (p106_poolB_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p106_DMSO_beta, pseudo_freq), na.rm = TRUE )) %>% ungroup () %>% mutate (log2fc_poolA_vs_dmso = log2 (poolA_vs_dmso_fc),log2fc_poolB_vs_dmso = log2 (poolB_vs_dmso_fc),max_log2fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ log2fc_poolA_vs_dmso,>= log2fc_poolA_vs_dmso ~ log2fc_poolB_vs_dmso),max_fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ poolA_vs_dmso_fc,>= log2fc_poolA_vs_dmso ~ poolB_vs_dmso_fc))
Save data
write.csv (p106_betas, "p106_betas_merged_Part1.csv" , row.names = FALSE )
Compile P108’s data
Load longitudinal frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/108pre-treatment_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/108pre-vaccine_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/108post-vaccine_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/108-Wk32d1_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )
Aggregate beta chains into one dataframe
<- p108_pretreatment_beta %>% full_join (p108_prevax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p108_pretreatment" = "Freq.x" ,"p108_prevax" = "Freq.y" ,"p108_pretreatment_umi" = "totalUMICount.x" ,"p108_prevax_umi" = "totalUMICount.y" %>% full_join (p108_postvax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p108_postvax" = "Freq" ,"p108_postvax_umi" = "totalUMICount" ) %>% full_join (p108_w32_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p108_w32" = "Freq" ,"p108_w32_umi" = "totalUMICount" ) %>% select ("v_hit" , "j_hit" , "cdr3" , "p108_pretreatment" , "p108_pretreatment_umi" , "p108_prevax" , "p108_prevax_umi" , "p108_postvax" , "p108_postvax_umi" , "p108_w32" , "p108_w32_umi" ) %>% mutate_at (c ("p108_pretreatment" , "p108_pretreatment_umi" , "p108_prevax" , "p108_prevax_umi" , "p108_postvax" , "p108_postvax_umi" , "p108_w32" , "p108_w32_umi" ), as.numeric) %>% unite ("Beta_clonotype" , c (v_hit, j_hit, cdr3), sep = ";" )dim (p108_betas_pbmc)
Calculate fold changes across longitudinal timepoints
<- p108_betas_pbmc %>% mutate (postvax_vs_prevax_fc = p108_postvax/ p108_prevax,prevax_vs_pretreatment_fc = p108_prevax/ p108_pretreatment,log2fc_postvax_vs_prevax = log2 (postvax_vs_prevax_fc),log2fc_prevax_vs_pretreatment = log2 (prevax_vs_pretreatment_fc))
Load in vitro frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/108-DMSO_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/108-PoolA-B_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/108-PoolB_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )
Aggregate beta chains into one dataframe
<- full_join (p108DMSO_beta,p108poolA_beta,by= "Beta_clonotype" ) %>% :: rename ("p108_DMSO_beta" = Freq.x,"p108_DMSO_umi" = totalUMICount.x, "p108_poolA_beta" = Freq.y,"p108_poolA_umi" = totalUMICount.y) %>% full_join (p108poolB_beta,by= "Beta_clonotype" ) %>% :: rename ("p108_poolB_beta" = Freq,"p106_poolB_umi" = totalUMICount)%>% distinct (Beta_clonotype) %>% dplyr:: count ()
Convert to decimal frequency to %
<- p108_betas_pbmc %>% mutate (p108_pretreatment = p108_pretreatment * 100 ,p108_postvax = p108_postvax * 100 ,p108_prevax = p108_prevax * 100 ,p108_w32 = p108_w32 * 100 )<- p108_betas_invitro %>% mutate (p108_DMSO_beta = p108_DMSO_beta * 100 ,p108_poolA_beta = p108_poolA_beta * 100 ,p108_poolB_beta = p108_poolB_beta * 100 )
Join longitudinal and in vitro frequencies by beta chain
<- full_join (p108_betas_pbmc, p108_betas_invitro)
Joining with `by = join_by(Beta_clonotype)`
Calculate fold changes across in vitro samples
<- p108_betas %>% rowwise () %>% mutate (poolA_vs_dmso_fc = sum (c (p108_poolA_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p108_DMSO_beta, pseudo_freq), na.rm = TRUE ),poolB_vs_dmso_fc = sum (c (p108_poolB_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p108_DMSO_beta, pseudo_freq), na.rm = TRUE )) %>% ungroup () %>% mutate (log2fc_poolA_vs_dmso = log2 (poolA_vs_dmso_fc),log2fc_poolB_vs_dmso = log2 (poolB_vs_dmso_fc),max_log2fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ log2fc_poolA_vs_dmso,>= log2fc_poolA_vs_dmso ~ log2fc_poolB_vs_dmso),max_fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ poolA_vs_dmso_fc,>= log2fc_poolA_vs_dmso ~ poolB_vs_dmso_fc))
Attach TCR reactivities to dataframe via the beta clonotype
<- reactivity %>% filter (Patient == "108" )<- p108_betas %>% mutate (Reactive = case_when (Beta_clonotype %in% p108_reactive$ Beta_clonotype ~ TRUE ,! (Beta_clonotype %in% p108_reactive$ Beta_clonotype) ~ FALSE ))
Save data
write.csv (p108_betas, "p108_betas_merged_Part1.csv" , row.names = FALSE )
Compile P109’s data
Load longitudinal frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/109pre-treament_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/109pre-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/109post-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/109wk48_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )
Aggregate beta chains into one dataframe
<- p109_pretreatment_beta %>% full_join (p109_prevax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p109_pretreatment" = "Freq.x" ,"p109_prevax" = "Freq.y" ,"p109_pretreatment_umi" = "totalUMICount.x" ,"p109_prevax_umi" = "totalUMICount.y" ) %>% full_join (p109_postvax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p109_postvax" = "Freq" ,"p109_postvax_umi" = "totalUMICount" ) %>% full_join (p109_w48_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p109_w48" = "Freq" ,"p109_w48_umi" = "totalUMICount" ) %>% select ("v_hit" , "j_hit" , "cdr3" , "p109_pretreatment" , "p109_pretreatment_umi" , "p109_prevax" , "p109_prevax_umi" , "p109_postvax" , "p109_postvax_umi" , "p109_w48" , "p109_w48_umi" ) %>% mutate_at (c ("p109_pretreatment" , "p109_pretreatment_umi" , "p109_prevax" , "p109_prevax_umi" , "p109_postvax" , "p109_postvax_umi" , "p109_w48" , "p109_w48_umi" ), as.numeric) %>% unite ("Beta_clonotype" , c (v_hit, j_hit, cdr3), sep = ";" )dim (p109_betas_pbmc)
Calculate fold changes across longitudinal timepoints
<- p109_betas_pbmc %>% mutate (postvax_vs_prevax_fc = p109_postvax/ p109_prevax,prevax_vs_pretreatment_fc = p109_prevax/ p109_pretreatment,log2fc_postvax_vs_prevax = log2 (postvax_vs_prevax_fc),log2fc_prevax_vs_pretreatment = log2 (prevax_vs_pretreatment_fc))
Load in vitro frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/18279-109DMSO_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/18279-109PoolA_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/18279-109PoolB_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )
Aggregate beta chains into one dataframe
<- full_join (p109DMSO_beta,p109poolA_beta,by= "Beta_clonotype" ) %>% :: rename ("p109_DMSO_beta" = Freq.x, "p109_poolA_beta" = Freq.y,"p109_DMSO_umi" = totalUMICount.x,"p109_poolA_umi" = totalUMICount.y) %>% full_join (p109poolB_beta,by= "Beta_clonotype" ) %>% :: rename ("p109_poolB_beta" = Freq,"p109_poolB_umi" = totalUMICount)%>% distinct (Beta_clonotype) %>% dplyr:: count ()
Convert to decimal frequency to %
<- p109_betas_pbmc %>% mutate (p109_pretreatment = p109_pretreatment * 100 ,p109_postvax = p109_postvax * 100 ,p109_prevax = p109_prevax * 100 ,p109_w48 = p109_w48 * 100 )<- p109_betas_invitro %>% mutate (p109_DMSO_beta = p109_DMSO_beta * 100 ,p109_poolA_beta = p109_poolA_beta * 100 ,p109_poolB_beta = p109_poolB_beta * 100 )
Join longitudinal and in vitro frequencies by beta chain
<- full_join (p109_betas_pbmc, p109_betas_invitro)
Joining with `by = join_by(Beta_clonotype)`
Calculate fold changes across in vitro samples
<- p109_betas %>% rowwise () %>% mutate (poolA_vs_dmso_fc = sum (c (p109_poolA_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p109_DMSO_beta, pseudo_freq), na.rm = TRUE ),poolB_vs_dmso_fc = sum (c (p109_poolB_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p109_DMSO_beta, pseudo_freq), na.rm = TRUE )) %>% ungroup () %>% mutate (log2fc_poolA_vs_dmso = log2 (poolA_vs_dmso_fc),log2fc_poolB_vs_dmso = log2 (poolB_vs_dmso_fc),max_log2fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ log2fc_poolA_vs_dmso,>= log2fc_poolA_vs_dmso ~ log2fc_poolB_vs_dmso),max_fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ poolA_vs_dmso_fc,>= log2fc_poolA_vs_dmso ~ poolB_vs_dmso_fc))
Save data
write.csv (p109_betas, "p109_betas_merged_Part1.csv" , row.names = FALSE )
Compile P110’s data
Load longitudinal frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/110pre-treat_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/110pre-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/110post-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/110wk38_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )
Aggregate beta chains into one dataframe
<- p110_pretreatment_beta %>% full_join (p110_prevax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p110_pretreatment" = "Freq.x" ,"p110_prevax" = "Freq.y" ,"p110_pretreatment_umi" = "totalUMICount.x" ,"p110_prevax_umi" = "totalUMICount.y" ) %>% full_join (p110_postvax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p110_postvax" = "Freq" ,"p110_postvax_umi" = "totalUMICount" ) %>% full_join (p110_w38_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p110_w38" = "Freq" ,"p110_w38_umi" = "totalUMICount" ) %>% select ("v_hit" , "j_hit" , "cdr3" , "p110_pretreatment" , "p110_pretreatment_umi" , "p110_prevax" , "p110_prevax_umi" , "p110_postvax" , "p110_postvax_umi" , "p110_w38" , "p110_w38_umi" ) %>% mutate_at (c ("p110_pretreatment" , "p110_pretreatment_umi" , "p110_prevax" , "p110_prevax_umi" , "p110_postvax" , "p110_postvax_umi" , "p110_w38" , "p110_w38_umi" ), as.numeric) %>% unite ("Beta_clonotype" , c (v_hit, j_hit, cdr3), sep = ";" )dim (p110_betas_pbmc)
Calculate fold changes across longitudinal timepoints
<- p110_betas_pbmc %>% mutate (postvax_vs_prevax_fc = p110_postvax/ p110_prevax,prevax_vs_pretreatment_fc = p110_prevax/ p110_pretreatment,log2fc_postvax_vs_prevax = log2 (postvax_vs_prevax_fc),log2fc_prevax_vs_pretreatment = log2 (prevax_vs_pretreatment_fc))
Load in vitro frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/110DMSO_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/110PoolA_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/110PoolB_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )
Aggregate beta chains into one dataframe
<- full_join (p110DMSO_beta,p110poolA_beta,by= "Beta_clonotype" ) %>% :: rename ("p110_DMSO_beta" = Freq.x, "p110_poolA_beta" = Freq.y,"p110_DMSO_umi" = totalUMICount.x,"p110_poolA_umi" = totalUMICount.y) %>% full_join (p110poolB_beta,by= "Beta_clonotype" ) %>% :: rename ("p110_poolB_beta" = Freq,"p110_poolB_umi" = totalUMICount)%>% distinct (Beta_clonotype) %>% dplyr:: count ()
Convert to decimal frequency to %
<- p110_betas_pbmc %>% mutate (p110_pretreatment = p110_pretreatment * 100 ,p110_postvax = p110_postvax * 100 ,p110_prevax = p110_prevax * 100 ,p110_w38 = p110_w38 * 100 )<- p110_betas_invitro %>% mutate (p110_DMSO_beta = p110_DMSO_beta * 100 ,p110_poolA_beta = p110_poolA_beta * 100 ,p110_poolB_beta = p110_poolB_beta * 100 )
Join longitudinal and in vitro frequencies by beta chain
<- full_join (p110_betas_pbmc, p110_betas_invitro)
Joining with `by = join_by(Beta_clonotype)`
Calculate fold changes across in vitro samples
<- p110_betas %>% rowwise () %>% mutate (poolA_vs_dmso_fc = sum (c (p110_poolA_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p110_DMSO_beta, pseudo_freq), na.rm = TRUE ),poolB_vs_dmso_fc = sum (c (p110_poolB_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p110_DMSO_beta, pseudo_freq), na.rm = TRUE )) %>% ungroup () %>% mutate (log2fc_poolA_vs_dmso = log2 (poolA_vs_dmso_fc),log2fc_poolB_vs_dmso = log2 (poolB_vs_dmso_fc),max_log2fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ log2fc_poolA_vs_dmso,>= log2fc_poolA_vs_dmso ~ log2fc_poolB_vs_dmso),max_fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ poolA_vs_dmso_fc,>= log2fc_poolA_vs_dmso ~ poolB_vs_dmso_fc))
Save data
write.csv (p110_betas, "p110_betas_merged_Part1.csv" , row.names = FALSE )
Compile P111’s data
Load longitudinal frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/111pre-treat_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/111pre-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/111post-vax_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/111wk40_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" )
Aggregate beta chains into one dataframe
<- p111_pretreatment_beta %>% full_join (p111_prevax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p111_pretreatment" = "Freq.x" ,"p111_prevax" = "Freq.y" ,"p111_pretreatment_umi" = "totalUMICount.x" ,"p111_prevax_umi" = "totalUMICount.y" ) %>% full_join (p111_postvax_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p111_postvax" = "Freq" ,"p111_postvax_umi" = "totalUMICount" ) %>% full_join (p111_w40_beta, by = c ("v_hit" , "j_hit" , "cdr3" )) %>% :: rename ("p111_w40" = "Freq" ,"p111_w40_umi" = "totalUMICount" ) %>% select ("v_hit" , "j_hit" , "cdr3" , "p111_pretreatment" , "p111_pretreatment_umi" , "p111_prevax" , "p111_prevax_umi" , "p111_postvax" , "p111_postvax_umi" , "p111_w40" , "p111_w40_umi" ) %>% mutate_at (c ("p111_pretreatment" , "p111_pretreatment_umi" , "p111_prevax" , "p111_prevax_umi" , "p111_postvax" , "p111_postvax_umi" , "p111_w40" , "p111_w40_umi" ), as.numeric) %>% unite ("Beta_clonotype" , c (v_hit, j_hit, cdr3), sep = ";" )dim (p111_betas_pbmc)
Calculate fold changes across longitudinal timepoints
<- p111_betas_pbmc %>% mutate (postvax_vs_prevax_fc = p111_postvax/ p111_prevax,prevax_vs_pretreatment_fc = p111_prevax/ p111_pretreatment,log2fc_postvax_vs_prevax = log2 (postvax_vs_prevax_fc),log2fc_prevax_vs_pretreatment = log2 (prevax_vs_pretreatment_fc))
Load in vitro frequencies
<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/111-DMSO_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/111-PoolA_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )<- read.csv ("/jsimonlab/projects/Wu/Melanoma_bulkTCR_Eryn/mixcr_processed_031324/Eryn_bulkrhTCR/111-PoolB_TRB_report.tsv" , sep = " \t " , row.names = 1 ) %>% select (aaSeqCDR3, vGene, jGene, totalUMICount, Freq) %>% :: rename ("cdr3" = "aaSeqCDR3" , "v_hit" = "vGene" , "j_hit" = "jGene" ) %>% unite ("Beta_clonotype" , c (v_hit,j_hit,cdr3),sep= ";" )
Aggregate beta chains into one dataframe
<- full_join (p111DMSO_beta,p111poolA_beta,by= "Beta_clonotype" ) %>% :: rename ("p111_DMSO_beta" = Freq.x,"p111_poolA_beta" = Freq.y,"p111_DMSO_umi" = totalUMICount.x,"p111_poolA_umi" = totalUMICount.y) %>% full_join (p111poolB_beta,by= "Beta_clonotype" ) %>% :: rename ("p111_poolB_beta" = Freq,"p111_poolB_umi" = totalUMICount)%>% distinct (Beta_clonotype) %>% dplyr:: count ()
Convert to decimal frequency to %
<- p111_betas_pbmc %>% mutate (p111_pretreatment = p111_pretreatment * 100 ,p111_postvax = p111_postvax * 100 ,p111_prevax = p111_prevax * 100 ,p111_w40 = p111_w40 * 100 )<- p111_betas_invitro %>% mutate (p111_DMSO_beta = p111_DMSO_beta * 100 ,p111_poolA_beta = p111_poolA_beta * 100 ,p111_poolB_beta = p111_poolB_beta * 100 )
Join longitudinal and in vitro frequencies by beta chain
<- full_join (p111_betas_pbmc, p111_betas_invitro)
Joining with `by = join_by(Beta_clonotype)`
Calculate fold changes across in vitro samples
<- p111_betas %>% rowwise () %>% mutate (poolA_vs_dmso_fc = sum (c (p111_poolA_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p111_DMSO_beta, pseudo_freq), na.rm = TRUE ),poolB_vs_dmso_fc = sum (c (p111_poolB_beta, pseudo_freq), na.rm = TRUE )/ sum (c (p111_DMSO_beta, pseudo_freq), na.rm = TRUE )) %>% ungroup () %>% mutate (log2fc_poolA_vs_dmso = log2 (poolA_vs_dmso_fc),log2fc_poolB_vs_dmso = log2 (poolB_vs_dmso_fc),max_log2fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ log2fc_poolA_vs_dmso,>= log2fc_poolA_vs_dmso ~ log2fc_poolB_vs_dmso),max_fc_pool_vs_dmso = case_when (log2fc_poolA_vs_dmso > log2fc_poolB_vs_dmso ~ poolA_vs_dmso_fc,>= log2fc_poolA_vs_dmso ~ poolB_vs_dmso_fc))
Save data
write.csv (p111_betas, "p111_betas_merged_Part1.csv" , row.names = FALSE )
Get session info
R version 4.3.2 (2023-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Rocky Linux 8.10 (Green Obsidian)
Matrix products: default
BLAS/LAPACK: /usr/lib64/libopenblasp-r0.3.15.so; LAPACK version 3.9.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: America/New_York
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] lubridate_1.9.4 forcats_1.0.0 stringr_1.5.1 purrr_1.0.4
[5] readr_2.1.5 tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.1
[9] tidyverse_2.0.0 dplyr_1.1.4
loaded via a namespace (and not attached):
[1] gtable_0.3.6 jsonlite_1.8.9 compiler_4.3.2 tidyselect_1.2.1
[5] scales_1.3.0 fastmap_1.2.0 R6_2.6.1 generics_0.1.3
[9] knitr_1.49 htmlwidgets_1.6.4 munsell_0.5.1 pillar_1.10.1
[13] tzdb_0.5.0 rlang_1.1.5 stringi_1.8.4 xfun_0.50
[17] timechange_0.3.0 cli_3.6.3 withr_3.0.2 magrittr_2.0.3
[21] digest_0.6.37 grid_4.3.2 rstudioapi_0.17.1 hms_1.1.3
[25] lifecycle_1.0.4 vctrs_0.6.5 evaluate_1.0.1 glue_1.8.0
[29] colorspace_2.1-1 rmarkdown_2.29 tools_4.3.2 pkgconfig_2.0.3
[33] htmltools_0.5.8.1